code: def test_accuracy(data, keras_model, hls_model):
      X = data
      model = keras_model
  
      # Model under test predictions and accuracy
      y_keras = model.predict(X)
      y_hls4ml = hls_model.predict(X)
  
      # "Accuracy" of hls4ml predictions vs keras
      rel_acc = accuracy_score(
          np.argmax(y_keras, axis=1), np.argmax(y_hls4ml, axis=1)
      )
      print(f"hls4ml accuracy relative to keras: {rel_acc}")
      assert rel_acc > 0.98
  
file_path: hls4ml/test/pytest/test_conv1d.py
imports: from pathlib import Path
  import numpy
  import pytest
  from sklearn.metrics import accuracy_score
  from tensorflow.keras.models import model_from_json
  import hls4ml
label_desc: Use image node_id 4 for calling a global function with example usage: test_accuracy(data, keras_model, hls_model) without return types